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Related lectures (34)

Projected Gradient Descent Log in to Mediaspace to watch this video

Explores convex constrained optimization through Projected Gradient Descent, focusing on tangent space and iterative minimization.

Convex Sets: Theory and Applications Log in to Mediaspace to watch this video

Explores convex sets, their properties, and applications in optimization.

Conjugate Duality: Understanding Convex Optimization Log in to Mediaspace to watch this video

Explores conjugate duality in convex optimization, covering weak and supporting hyperplanes, subgradients, duality gap, and strong duality conditions.

Faster Gradient Descent: Projected Optimization Techniques Log in to Mediaspace to watch this video

Covers faster gradient descent methods and projected gradient descent for constrained optimization in machine learning.

KKT for convex problems and Slater's CQ Log in to Mediaspace to watch this video

Covers the KKT conditions and Slater's condition in convex optimization problems.

Convex Optimization Log in to Mediaspace to watch this video

Introduces convex optimization, focusing on the importance of convexity in algorithms and optimization problems.

Optimal Transport: Gradient Flows in Rd Log in to Mediaspace to watch this video

Explores optimal transport and gradient flows in Rd, emphasizing convergence and the role of Lipschitz and Picard-Lindelöf theorems.

Geodesically Convex Optimization Log in to Mediaspace to watch this video

Covers geodesically convex optimization on Riemannian manifolds, exploring convexity properties and minimization relationships.

Linear Programming Basics Log in to Mediaspace to watch this video

Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.

Convexity: Functions and Global Minima Log in to Mediaspace to watch this video

Explores convex functions, global minima, and their relationship with differentiability.

Convex Functions: Theory and Applications Log in to Mediaspace to watch this video

Explores convex functions, affine transformations, pointwise maximum, minimization, Schur's Lemma, and relative entropy in mathematical optimization.

Variational Problems: Convexity and Coercivity Log in to Mediaspace to watch this video

Explores variational problems, emphasizing convexity and coercivity conditions in functionals with integral side constraints.

Convex Optimization: Portfolio Optimization Log in to Mediaspace to watch this video

Covers Distributionally Robust Portfolio Optimization for maximizing expected utility with uncertain asset returns.

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